42 research outputs found

    Development of a high-resolution NGS-based HLA-typing and analysis pipeline

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    The human leukocyte antigen (HLA) complex contains the most polymorphic genes in the human genome. The classical HLA class I and II genes define the specificity of adaptive immune responses. Genetic variation at the HLA genes is associated with susceptibility to autoimmune and infectious diseases and plays a major role in transplantation medicine and immunology. Currently, the HLA genes are characterized using Sanger- or next-generation sequencing (NGS) of a limited amplicon repertoire or labeled oligonucleotides for allele-specific sequences. High-quality NGS-based methods are in proprietary use and not publicly available. Here, we introduce the first highly automated open-kit/open-source HLA-typing method for NGS. The method employs in-solution targeted capturing of the classical class I (HLA-A, HLA-B, HLA-C) and class II HLA genes (HLA-DRB1, HLA-DQA1, HLA-DQB1, HLA-DPA1, HLA-DPB1). The calling algorithm allows for highly confident allele-calling to three-field resolution (cDNA nucleotide variants). The method was validated on 357 commercially available DNA samples with known HLA alleles obtained by classical typing. Our results showed on average an accurate allele call rate of 0.99 in a fully automated manner, identifying also errors in the reference data. Finally, our method provides the flexibility to add further enrichment target regions

    Tolerating Faults in Counting Networks

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    Counting networks were proposed by Aspnes, Herlihy and Shavit [4] as a technique for solving multiprocessor coordination problems. We describe a method for tolerating an arbitrary number of faults in counting networks. In our fault model, the following errors can occur dynamically in the counting network data structure: 1) a balancer's state is spuriously altered, 2) a balancer's state can no longer be accessed. We propose two approaches for tolerating faults. The first is based on a construction for a fault-tolerant balancer. We substitute a fault-tolerant balancer for every balancer in a counting network. Thus, we transform a counting network with depth O(log to the power of 2 n); where n is the width, into a k-fault-tolerant counting network with depth O(k log to the power of 2 n). The second approach is to append a correction network, built with fault-tolerant balancers, to a counting network that may experience faults. We present a bound on the error in the output token distribution of counting networks with faulty balancers (a generalization of the error bound for sorting networks with faulty comparators presented by Yao & Yao [21]. Given a token distribution with a bounded error, the correction network produces a token distribution that is smooth, i.e., the number of tokens on each output wire differs by at most one (a weaker condition than the step property). In order to tolerate k faults, the correction network has depth O (k to the power of 2 log n) for a network of width n

    A morphological approach to Hough transform on an instruction systolic array

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    Instruction systolic arrays have been developed in order to combine the speed and the simplicity of systolic arrays with the flexibility of MIMD parallel computer systems. Instruction systolic arrays are available as quadratic arrays of small RISC processors capable of performing integer and floating point arithmetic. In this paper a new algorithm for line detection is presented which applies the morphological approach to the well-known Hough transform. The quality of its results is significantly higher than that of the classical Hough transform. Our algorithm has an AT-complexity of O(N3). This matches the one of the best known alternatives in the literature. It will be shown that the new algorithm is more efficient in practical applications. It has been tailored towards the capabilities of the instruction systolic array. This leads to a high-speed implementation on Systola 1024, the first low cost parallel computer of this particular architecture on the market

    Systolic algorithm for tensor products of matrices: implementation and applications

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    Tensor products of matrices play a very important role in approximation and interpolation. This paper describes a systolic algorithm for tensor products in mesh connected arrays and the closely related hypercube architectures (including the Connection Machine). It is based on a new operator called bullet operator which is a higher dimensional matrix operation. The applications of tensor products to multivariable spline blending approximation as well as graphics/image processing are indicated

    BMA - Boolean matrices as model for motif kernels

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    PLUG: An Agent Based Prototype Validation of CAD-Constructions

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    A new approach for an automatic consistency check in the development of prototypes in the automotive industry is presented. It is based on the observation that inconsistencies between adjacent parts of the prototype can be located at the plugs connecting these parts. This paper describes the PLUG software system whose idea is to assign intelligence to every plug in the system in order to continuously monitor the consistency of the overall design of the prototype. It has been implemented as a multi agent system where each agent is responsible for supervising a specific property of the parts adjacent to such a plug. The properties are structured according to the so called PLUG structural model which is a simple but powerful set theoretical representation of the interaction between adjacent parts

    Sorting on a three dimensional cube grid

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    SIGLECopy held by FIZ Karlsruhe; available from UB/TIB Hannover / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

    Fast sorting on the instruction systolic array

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    SIGLECopy held by FIZ Karlsruhe; available from UB/TIB Hannover / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman
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